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        Lecturer(s)
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                    Konečný Jan, doc. RNDr. Ph.D.
                
 
            
         
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        Course content
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        Structures of truth degrees: Residuated lattices and their properties. Subclasses of residuated lattices given by identities: MTL-algebras, BL-algebras, MV-algebras, G-algebras, Pi-algebras, and others. Filters on residuated lattices. Subdirect representation of MTL and BL-algebras.  Propositional BL-logic and its schematic extensions: Language of BL-logic, formulas, axiomatic systems. Derived logical connectives. Provability, deduction theorem. Soundness and completeness of   BL-logic. Schematic extensions, Lukasiewicz logic, Goedel logic, product logic, and their standard completeness.  Pavelka's abstract logic: Logic with truth-weighted syntax. Theories as fuzzy sets of formulas. Truth-weighted proofs and provability degrees. General concepts of soundness and completeness in Pavelka-style logics. Examples of Pavelka-complete calculi: propositional Pavelka Rational Logic (RPL) and its completeness (via BL).  Predicate BL-logic and further logics: Fuzzy structures and safe interpretations. Completeness of predicate BL-logic. Propositional and predicate MTL-logic. Extension of fuzzy logics by unary connectives (Baaz's delta connective). Fuzzy logic vs. modalities and generalized quantifiers. Fuzzy logic calculi over restricted types of formulas: fuzzy equational logic, fuzzy horn logic, logic of fuzzy attribute implications.  Fuzzy structures and their properties: Fuzzy sets and fuzzy relations (in naive sense) as particular fuzzy structures. Properties of fuzzy structures. Representation of fuzzy structures by classical sets (cutlike representation). Special fuzzy relations: similarity and fuzzy equality. Compatibility and similarity preservation. Cutlike semantics. 
         
         
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        Learning activities and teaching methods
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        Lecture, Demonstration
        
            
                    
                
                    
                    - Preparation for the Exam
                        - 120 hours per semester
                    
 
                
             
        
        
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                Learning outcomes
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                The students become familiar with basic concepts of fuzzy logic. 
                 
                1. Knowledge Describe and understand comprehensively principles and methods of fuzzy logic.
                 
                
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                Prerequisites
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                unspecified
                
                
                    
                        
                    
                    
                
                
  
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                Assessment methods and criteria
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                        Oral exam, Written exam
                        
                        
                         
                        
                    
                    
                
                 Active participation in class. Completion of assigned homeworks. Passing the oral (or written) exam.
                 
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        Recommended literature
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                    Bělohlávek R. (2002). Fuzzy Relational Systems: Foundations and Principles. NY: Kluwer Academic/Plenum Press (Vol.20 of IFSR Int. Series on Systems Science and Engineering). 
                
 
            
                
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                    Bělohlávek R., Vychodil V. (2005). Fuzzy Equational Logic. Springer-Verlag. 
                
 
            
                
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                    Gerla G. (2001). Fuzzy Logic. Mathematical Tools for Approximate Reasoning. Kluwer, Dordrecht. 
                
 
            
                
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                    Gottwald S. (2001). A Treatise on Many-Valued Logics. Taylor & Francis Group. 
                
 
            
                
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                    Hájek P. (1998). Metamathematics of Fuzzy Logic. Kluwer, Dordrecht. 
                
 
            
                
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                    Klement E. P., Mesiar R., Pap E. (2000). Triangular Norms. Kluwer, Dordrecht. 
                
 
            
                
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                    Klir G. J., Yuan B. (1995). Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice-Hall. 
                
 
            
         
         
         
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